Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors. The existing staging system has a limited budget capacity for HCC recurrence. The authors aimed to establish and verify two nomogram models to predict disease-free survival (DFS) and overall survival (OS) in patients with HCC. Methods: Patients diagnosed with HCC between August 2011 and March 2016 were recruited. Data were randomly divided into a training cohort and a validation cohort. Based on univariate and multivariate Cox regression analysis, independent risk factors for DFS and OS were identified, and two nomogram models were established to predict patient survival. Results: Sex, tumor size, Barcelona Clinic Liver Cancer (BCLC) stage, tumor capsule, macrovascular invasion, AST-to-platelet ratio index, AST-to-lymphocyte ratio index, neutrophil–lymphocyte ratio and alpha-fetoprotein (AFP) were used to build the nomogram for DFS, while age, tumor size, BCLC stage, tumor capsule, macrovascular invasion, systemic immune-inflammation index, AST, total bilirubin and AFP were used to build the nomogram for OS. Calibration curves showed good agreement between the nomogram prediction and actual observation. C-indices in both nomograms were significantly higher than BCLC. Conclusion: The two nomograms improved the accuracy of individualized prediction of DFS and OS, which may help doctors screen patients with a high risk of recurrence to formulate individualized treatment plans.
Tumor Size Drives the Prognosis After Hepatic Resection of Solitary Hepatocellular Carcinoma Without Vascular Invasion
